Display of visualizations of properties of very large datasets has been an area of interest for many years. For example, a user may wish to determine trends in voting habits, based on viewing a map of the United States that is somehow shaded (e.g., with shades of red or blue) or hatched to indicate polling results for various areas of the country. Datasets of records that include multiple attribute values (e.g., records representing people with attributes such as age, gender, ethnicity, eye color, hair color, education level, church membership, educational institutions, political voting habits, geographic location of residence, appraised value of home, etc.) may provide information of interest to many users. For example, many users may wish to determine the number of men who voted for a particular political candidate, versus the number of women who voted for the candidate, while focusing on which areas of the country had significant differences in such voting statistics from other areas of the country. For example, a further focus may involve adding ethnicity into the statistical parameters for such a determination. Many users (e.g., political candidates) may further wish to focus on more dense or less dense areas to select one or more individual citizens, to study the individuals themselves in more depth (e.g., to ask them to appear at campaign events).